MS python学习（18）

学习Pandas.DataFrame(2)

load csv(comma seperated variable) files to DataFrame and vice versa

upload csv files
read/write csv files

1. load data into jupyter notebook, create a new folder and then upload the csv files into it. (CSV = comma seperated variable) 文件格式如下：

   Name,City,Country    # first line is column names
   Seattle-Tacoma,Seattle,USA
   Dulles,Washington,USA
   Heathrow,London,United Kingdom
   Schiphol,Amsterdam,Netherlands
   Changi,Singapore,Singapore
   Pearson,Toronto,Canada
   Narita,Tokyo,Japan
   

   

2. Normal csv files:

   dataframe = pd.read_csv(‘Folder/name.csv’)

   

3. csv files had bad lines:

   dataframe = pd.read_csv(‘Folder/name.csv’, on_bad_lines='skip')

   注意error_bad_lines=False 这个参数在pandas 1.3后就不用了

   第四行多了一个comma,直接读取会报错，加了on_bad_lines='skip'

   后这一行就不会读取，另外如果有空值的地方会直接显示为NaN
   

4. csv fiels do not have column headers:

   dataframe = pd.read_csv(‘Folder/name.csv’, header=None) (column name变为0,1,2…)

   dataframe = pd.read_csv(‘Folder/name.csv’, header=None,Name=['name1','name2','name3'...])(Name参数指定column name)

5. 将DataFrame 导出为csv files

   dataframe.to_csv(‘NewName.csv’) – 默认会把行号也导入进去

   dataframe.to_csv(‘NewName.csv’, index=False) – 不导入行号

TO BE CONTINUED…